Today's portable electronic devices, for example, smartphones and wearable devices may contain multiple sensors, which enhance the user experience. Usually such device includes at least an accelerometer. The most common form of mobile computing in use today is the smartphone. These may have a number of different sensors implemented initially to improve the user experience such as using the accelerometer to measure changes in screen orientation or the magnetometer to support location and navigation applications. These sensors can also be used to collect data that helps to understand human behavior, recognize specific activities, augment human memory of events, improve sporting performance and provide support for different therapies including both body movement and sleep disorders.
There are applications for portable electronic devices that use, or could use some data regarding user's current activity that can be gathered from the sensors, but this requires from the application developers the competence and additional resources needed to develop new sensor algorithms. Program developers do not have many options of activity recognition algorithms to choose from. Either the developers create and implement their own activity recognition algorithm, or they use activity recognition algorithm of operation system, if it supplies one.
Based on the above, there is a need for a solution that would enable more efficient and versatile use of activity recognition algorithms.